Background
Chromosome 22q11.2 Deletion Syndrome (22q11DS) is the most frequent microdeletion syndrome in humans with an estimated prevalence of 1:3000-1:6000 live births [
1]-[
4]. A wide array of phenotypes has been associated with this syndrome including structural malformations (congenital heart disease (CHD), thyroid abnormalities, and hypocalcemia) and neurodevelopmental and neurological deficits (Intellectual Disabilities (ID), Attention Deficit Hyperactivity Disorder (ADHD) and seizures) [
5].
The majority of 22q11 deletions arise
de novo (90%) and only a small minority (10%) is inherited. The high frequency of
de novo events has been attributed to the high mutation-rearrangement rate associated with several low copy repeat (LCR) regions throughout the 22q deletion region [
6],[
7]. The LCRs found in 22q are larger and have higher sequence similarity than most other LCR regions in the genome, possibly explaining the higher prevalence of 22q11DS in the general population compared to other chromosomal deletion syndromes [
8],[
9]. It is thought that the majority of individuals with 22q11DS have deletion breakpoints located within the 22q11 LCRs. Indeed, 70-80% of these individuals have the 3 Mb deletion (between LCR A and D), 10-15% have a nested 1.5 Mb deletion (between LCR A and B), and the remaining have atypical deletions [
7],[
10]-[
33]. These deletions are likely the results of unequal crossing-over during meiosis involving smaller LCRs within the deleted regions.
Multiple studies have attempted to delineate the deletion endpoints in individuals with 22q11DS; however, the difficulty in designing unique primers or identifying unique SNPs in the proximity or within these repeat regions has hindered the progress of locating the exact position of the deletion endpoints which remains poorly defined [
10],[
34]-[
36].
Several studies have also attempted to elucidate genotype-phenotype correlations among individuals with 22q11DS or to identify a minimal region of disease, but these correlations are still not well understood [
12],[
15]. Reports of individuals with different size deletions that cover nearby, non-overlapping regions and presenting with similar clinical phenotypes stress the importance of delineating the exact deletion endpoints in order to accurately bin individuals and specific phenotypes. Specifically, Amati et al. [
14] and Yamagishi et al. [
20] described several cases with different, adjacent deletions located between LCR-A and LCR-B that presented with CHD and facial dysmorphism. These observations suggest that a minimal critical region for these phenotypes that exists between LCR-A and LCR-B. The need for better genotype and phenotype correlations in individuals with 22q11DS makes it important to screen a large cohort with high resolution in order to determine the exact deletion breakpoints and to correctly identify those regions that may correlate to specific phenotypes.
So far, the methodologies utilized for gene copy number quantification have often given inconsistent results in target populations. Currently, the gold standard method of diagnosis for 22q11DS is by fluorescent
in-situ hybridization (FISH) [
5],[
37]. However, this approach is labor intensive, expensive, requires specialized and well trained technicians and equipment, and may not identify a small portion of individuals with 22q11DS. In addition, it is difficult to adopt FISH in a high throughput setting. Other methodologies currently used to determine the presence of a deletion and to delineate the endpoints for 22q11DS include: multiplex ligation-dependent probe amplification (MLPA) [
38], quantitative PCR (qPCR) [
35], and multiple types of chromosomal arrays (single nucleotide polymorphisms microarrays, (SNPs) and array-based comparative genomic hybridization, aCGH) [
39]. However, none of these have been shown to be high-throughput, robust and cost-effective. Specifically, the high cost and technical complexity of the CGH array make it unsuitable for routine diagnostic use and for high throughput testing. Various steps have been found to be critical and limiting for the performance of MLPA including the choice of the reference DNA, incomplete denaturation, and sensitivity to DNA and salt concentration [
40],[
41]. Lastly, qPCR is prone to false positive results, perhaps due to the limited efficiency of the oligonucleotide probes, nucleotide content of the target region and susceptibility to inhibitors [
42],[
43].
Droplet digital PCR (ddPCR) is a new approach to nucleic acid detection and quantification and gives extremely robust values as samples are partitioned into approximately 20,000 water-in-oil droplets, allowing many thousands of discrete measurements to be made. Additionally, as the partitioning of a DNA sample allows for an independent reaction in each droplet, robust CN measurements with 95% confidence can be generated. The binary nature of ddPCR makes it tolerant to differences in PCR amplification efficiency, often allowing for no overlap of 95% confidence intervals for adjacent copy number states [
44] and has been demonstrated to possess a high level of accuracy and precision for determining copy number quantification [
45]. Finally, as multiplexing can be easily performed using ddPCR, the ~4$ cost per sample allows not only the detection of 22q11DS but simultaneously allows the differentiation between the two common deletions (3 Mb and 1.5 Mb).
In this study, we utilized ddPCR for CN value measurements at different locations within the 22q11.2 region to finely map the deletion breakpoints in 80 individuals with 22q11DS. We demonstrate that ddPCR is a precise and reliable approach for detecting CN variation within the 22q11 locus (using either Taqman or EvaGreen assays) and that ddPCR can be used to delineate the deletion endpoints, which may be helpful in identifying the critical regions corresponding to disease. We also used ddPCR to study genotype-phenotype correlations in 22q11DS and to examine its application for diagnostic and clinical purposes.
Conclusions
In this study we demonstrate the feasibility of ddPCR for detecting and mapping deletions of chromosome 22q11.2. While other methods have been used to elucidate deletion endpoints in individuals with 22q11DS, none have all the qualities required for an effective and reliable diagnostic tool. Additionally, clinical and molecular diagnostics require methodologies that are robust, cost effective and at high throughput.
Although it is not common medical practice to identify the extent of patients' deletions or the location, it may be important, in some cases, to better characterize the LCRs and individual's deletion, size and location. However, many of the genes involved in clinical phenotypes in 22q11DS appear to be located in the common 1.5 Mb deletion region between LCR A-B.
Our findings support the hypothesis that the majority of individuals with 22q11DS have deletion breakpoints located near or within LCRs A and D. Two individuals appear to have breakpoints localized within smaller LCRs scattered along chromosome 22.
Importantly, in this study we show that ddPCR is an ideal technology for detecting 22q11DS and can allow fine mapping of the deleted region using either TaqMan or EvaGreen assays and may be qualified for use in a clinical setting. ddPCR is a high throughput, cost effective technology that allows absolute measure of nucleic acid concentration, providing highly accurate estimations of DNA copy number. Approximately 200 samples can be easily run and analyzed daily, without the difficulties, ambiguity, time and cost of other methodologies, making ddPCR the preferred tool for determining DNA copy number variation in large population screening studies.
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Competing interests
Dr. Tassone has received funds from Roche. Dr. Angkustsiri is involved in clinical trials through Roche, Novartis, Seaside, Forest, and SynapDx.
Authors' contributions
VH performed the experiments and participated to the analysis and writing of the manuscript. DM performed the experiments, performed analysis and participated to the writing of the manuscript. JR performed analysis and participated to the writing of the manuscript. KA performed clinical evaluations of the participants in the study and participated in the writing of the manuscript. TS recruited individuals in the study and participated to the writing of the manuscript. FT conceived the study, its design, coordination and analysis and participated to the writing of the manuscript. All authors read and approved the final manuscript.